Information filtering and information retrieval: two sides of the same coin?
Communications of the ACM - Special issue on information filtering
The design of a high performance information filtering system
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Newsjunkie: providing personalized newsfeeds via analysis of information novelty
Proceedings of the 13th international conference on World Wide Web
An outranking approach for information retrieval
Information Retrieval
Nereau: a social approach to query expansion
Proceedings of the 10th ACM workshop on Web information and data management
Multidimensional Relevance: A New Aggregation Criterion
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
A new framework for analyzing political news
Proceedings of the 10th Annual International Conference on Digital Government Research: Social Networks: Making Connections between Citizens, Data and Government
A multimedia recommender integrating object features and user behavior
Multimedia Tools and Applications
Multidimensional relevance: Prioritized aggregation in a personalized Information Retrieval setting
Information Processing and Management: an International Journal
Interaction and personalization of criteria in recommender systems
UMAP'10 Proceedings of the 18th international conference on User Modeling, Adaptation, and Personalization
Proceedings of the 12th International Conference on Electronic Commerce: Roadmap for the Future of Electronic Business
Automated query learning with Wikipedia and genetic programming
Artificial Intelligence
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In this paper we present a novel filtering system, based on a new model which reshapes the aims of content-based filtering. The filtering system has been developed within the EC project PENG, aimed at providing news professionals, such as journalists, with a system supporting both filtering and retrieval capabilities. In particular, we suggest that in tackling the problem of information overload, it is necessary for filtering systems to take into account multiple aspects of incoming documents in order to estimate their relevance to a user's profile, and in order to help users better understand documents, as distinct from solely attempting to either select relevant material from a stream, or block inappropriate material. Aiming to so this, a filtering model based on multiple criteria has been defined, based on the ideas gleamed in the project requirements stage. The filtering model is briefly described in this paper.